Study of the DNA double helix will lead to transformative medical care and increasingly urgent questions about how to responsibly handle genetic engineering technology.
The news last November that a rogue Chinese scientist had genetically altered the embryos of a pair of Chinese twins shocked the world. But although this use of advanced technology to change the human gene pool was premature, it was a harbinger of how genetic science will alter our healthcare, the way we make babies, the nature of the babies we make, and, ultimately, our sense of who and what we are as a species.
The healthcare applications of the genetics revolution are merely stations along the way to the ultimate destination.
But while the genetics revolution has already begun, we aren't prepared to handle these Promethean technologies responsibly.
By identifying the structure of DNA in the 1950s, Watson, Crick, Wilkins, and Franklin showed that the book of life was written in the DNA double helix. When the human genome project was completed in 2003, we saw how this book of human life could be transcribed. Painstaking research paired with advanced computational algorithms then showed what increasing numbers of genes do and how the genetic book of life can be read.
Now, with the advent of precision gene editing tools like CRISPR, we are seeing that the book of life -- and all biology -- can be re-written. Biology is being recognized as another form of readable, writable, and hackable information technology with we humans as the coders.
The impact of this transformation is being first experienced in our healthcare. Gene therapies including those extracting, re-engineering, then reintroducing a person's own cells enhanced into cancer-fighting supercells are already performing miracles in clinical trials. Thousands of applications have already been submitted to regulators across the globe for trials using gene therapies to address a host of other diseases.
Recently, the first gene editing of cells inside a person's body was deployed to treat the genetically relatively simple metabolic disorder Hunter syndrome, with many more applications to come. These new approaches are only the very first steps in our shift from the current system of generalized medicine based on population averages to precision medicine based on each patient's individual biology to predictive medicine based on AI-generated estimations of a person's future health state.
Jamie Metzl's groundbreaking new book, Hacking Darwin: Genetic Engineering and the Future of Humanity, explores how the genetic revolution is transforming our healthcare, the way we make babies, and the nature of and babies we make, what this means for each of us, and what we must all do now to prepare for what's coming.
This shift in our healthcare will ensure that millions and then billions of people will have their genomes sequenced as the foundation of their treatment. Big data analytics will then be used to compare at scale people's genotypes (what their genes say) to their phenotypes (how those genes are expressed over the course of their lives).
These massive datasets of genetic and life information will then make it possible to go far beyond the simple genetic analysis of today and to understand far more complex human diseases and traits influenced by hundreds or thousands of genes. Our understanding of this complex genetic system within the vaster ecosystem of our bodies and the environment around us will transform healthcare for the better and help us cure terrible diseases that have plagued our ancestors for millennia.
But as revolutionary as this challenge will be for medicine, the healthcare applications of the genetics revolution are merely stations along the way to the ultimate destination – a deep and fundamental transformation of our evolutionary trajectory as a species.
A first inkling of where we are heading can be seen in the direct-to-consumer genetic testing industry. Many people around the world have now sent their cheek swabs to companies like 23andMe for analysis. The information that comes back can tell people a lot about relatively simple genetic traits like carrier status for single gene mutation diseases, eye color, or whether they hate the taste of cilantro, but the information about complex traits like athletic predisposition, intelligence, or personality style today being shared by some of these companies is wildly misleading.
This will not always be the case. As the genetic and health data pools grow, analysis of large numbers of sequenced genomes will make it possible to apply big data analytics to predict some very complex genetic disease risks and the genetic components of traits like height, IQ, temperament, and personality style with increasing accuracy. This process, called "polygenic scoring," is already being offered in beta stage by a few companies and will become an ever bigger part of our lives going forward.
The most profound application of all this will be in our baby-making. Before making a decision about which of the fertilized eggs to implant, women undergoing in vitro fertilization can today elect to have a small number of cells extracted from their pre-implanted embryos and sequenced. With current technology, this can be used to screen for single-gene mutation diseases and other relatively simple disorders. Polygenic scoring, however, will soon make it possible to screen these early stage pre-implanted embryos to assess their risk of complex genetic diseases and even to make predictions about the heritable parts of complex human traits. The most intimate elements of being human will start feeling like high-pressure choices needing to be made by parents.
The limit of our imagination will become the most significant barrier to our recasting biology.
Adult stem cell technologies will then likely make it possible to generate hundreds or thousands of a woman's own eggs from her blood sample or skin graft. This would blow open the doors of reproductive possibility and allow parents to choose embryos with exceptional potential capabilities from a much larger set of options.
The complexity of human biology will place some limits to the extent of possible gene edits that might be made to these embryos, but all of biology, including our own, is extremely flexible. How else could all the diversity of life have emerged from a single cell nearly four billion years ago? The limit of our imagination will become the most significant barrier to our recasting biology.
But while we humans are gaining the powers of the gods, we aren't at all ready to use them.
The same tools that will help cure our worst afflictions, save our children, help us live longer, healthier, more robust lives will also open the door to potential abuses. Prospective parents with the best of intentions or governments with lax regulatory structures or aggressive ideas of how population-wide genetic engineering might be used to enhance national competitiveness or achieve some other goal could propel us into a genetic arms race that could undermine our essential diversity, dangerously divide societies, lead to dangerous, destabilizing, and potentially even deadly conflicts between us, and threaten our very humanity.
But while the advance of genetic technologies is inevitable, how it plays out is anything but. If we don't want the genetic revolution to undermine our species or lead to grave conflicts between genetic haves and have nots or between societies opting in and those opting out, now is the time when we need to make smart decisions based on our individual and collective best values. Although the technology driving the genetic revolution is new, the value systems we will need to optimize the benefits and minimize the harms of this massive transformation are ones we have been developing for thousands of years.
And while some very smart and well-intentioned scientists have been meeting to explore what comes next, it won't be enough for a few of even our wisest prophets to make decisions about the future of our species that will impact everyone. We'll also need smart regulations on both the national and international levels.
Every country will need to have its own regulatory guidelines for human genetic engineering based on both international best practices and the country's unique traditions and values. Because we are all one species, however, we will also ultimately need to develop guidelines that can apply to all of us.
As a first step toward making this possible, we must urgently launch a global, species-wide education effort and inclusive dialogue on the future of human genetic engineering that can eventually inform global norms that will need to underpin international regulations. This process will not be easy, but the alternative of an unregulated genetic arms race would be far worse.
The overlapping genomics and AI revolutions may seem like distant science fiction but are closer than you think. Far sooner than most people recognize, the inherent benefits of these technologies and competition between us will spark rapid adoption. Before that spark ignites, we have a brief moment to come together as a species like we never have before to articulate and translate into action the future we jointly envision. The north star of our best shared values can help us navigate the almost unimaginable opportunities and very real challenges that lie ahead.
A recent study in The Lancet Oncology showed that AI found 20 percent more cancers on mammogram screens than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.